Publishing chemical structure data in the cloud comes with a large set of challenges, mostly related to the accurate representation of chemical structures, particularly with regard to stereochemistry. Publishing spectral data in the cloud comes with its own unique set of challenges. Since most spectra are paired with a corresponding chemical structure, all of the chemical structure data challenges come along for the ride.<br/><br/>The plethora of analytical techniques, spectral and chromatographic data file formats, variations in the metadata stored in those files, and even differences in the vocabulary used to describe these metadata make consistency problematic. Other complications include the multidimensionality of spectral data (for example, LC-MS or LC-MSn) and complex interrelationships between chromatograms, spectra, and chemical structures. The shear size of the raw data files raises the question of whether or not raw data should be stored, and if it should, raises the question of sustainability of the repository in which the data are stored. Finally, connecting the spectral data to the publications in which they appear is yet another problem to be solved.<br/><br/>This paper discusses the scope of these issues, describes how many of the issues have been solved, and provides a vision of how the as-yet unsolved issues can be addressed.

Publishing spectral data in the cloud

256th National Meeting (2018)

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